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# Senior Technical Architect

- **Company:** o9 Solutions
- **Location:** Dallas, TX, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Big Data, Unix, Cloud Computing, Information Systems, Customer Data Management, Data Architecture, Extract Transform Load (ETL), Data Transformation, Apache Hadoop, MapReduce, Apache Hive, Python (Programming Language), Unix Shell, Machine Learning, Microsoft SQL Server, SAP ERP, Natural Language Processing, Open Database Connectivity, Apache Oozie, Oracle (Applications), Performance Tuning, Systems Development Life Cycle, Scala (Programming Language), Software Engineering, SQL Stored Procedures, PL-SQL, Sqoop, Systems Integration, Teradata SQL, Test Data, Apache Zookeeper, Data Processing, Apache Yarn, Apache Spark, Generative AI, Information Technology, Data Analytics, Microservices
- **Published:** June 13, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=bf300316a739534d

## About the Role

Do you have experience in UNIX?

## Description

Senior Technical Architect needed by o9 Solutions, Inc. in Dallas, TX [& various unanticipated locations throughout the U.S.; may telecommute] to Collaborate with cross-functional teams, including data engineers, data scientists, and business stakeholders to validate, synthesize and transform customer data for integrated business planning and analytics. Review and analyze the data provided by customers along with its technical/functional intent and interdependencies. Participate in the technical design, data requirements gathering, and making recommendations in case of inaccurate or missing data. Design and automate the data loading and insights generation process with intelligent checks and balances for sustained value delivery. Identify and implement performance optimization strategies to enhance data processing and analytics capabilities. Design solutions for the performance problem mechanism regarding various DB technologies within various platforms. Create and execute test plans,
document issues and track progress at resolving issues. Provide technical leadership and guidance to development teams, ensuring adherence to architectural principles and best practices. Leverage machine learning for predictive modeling in data architecture performance and business planning. Implement automated data quality checks and anomaly detection using AI algorithms. Utilize Generative AI for synthesizing realistic, anonymized test data. Develop AI-driven resource allocation models to optimize cloud infrastructure costs based on anticipated data workloads. Integrate natural language processing (NLP) capabilities to analyze unstructured data sources for hidden business insights. Minimum Requirements: Requires a Bachelor's degree, or foreign equivalent degree in Computer Science, Software Engineering, Operations Research, Industrial Engineering, Engineering Management, Electrical Engineering, Electronics Engineering, Business Analytics, Engineering or Information Systems and 6 years
of progressive, post-baccalaureate experience in the job offered or 6 years of progressive, post-baccalaureate experience in a related occupation driving the SDLC with key emphasis on architecting, designing, and developing solutions using Big Data Technologies such as Hive; performing ETL development and designing ETL solutions for clients; building data ingress or egress pipelines, handling of huge volume of data and developing data transformation functions using languages such as Python, HQL, Spark; utilizing big data technologies such as Spark, Scala, and Hadoop; utilizing various Hadoop infrastructures such as Map Reduce, Hive, Sqoop, Zookeeper and Oozie; integrating various data sources definitions such as Teradata, SAP ERP, SQL Server, Oracle, ODBC connectors and Flat Files through API or batch; utilizing unix shell scripting; utilizing PL/SQL to write Stored Procedures, Functions and Triggers; utilizing Spark Context, Spark-SQL, Spark YARN to improve the performance and
optimization of the existing algorithms in Hadoop; and designing and deploying containerized micro services.


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